Metacognitive Management of Attention in Online Learning

Authors

by Matthew Jensen Hays¹ ,Scott Richard Kustes¹ and Elizabeth Ligon Bjork^2
1 Amplifire, Boulder, CO 80301, USA
² Department of Psychology, University of California, Los Angeles, Los Angeles, CA 90095, USA
^* Author to whom correspondence should be addressed.

Abstract

Performance during training is a poor predictor of long-term retention. Worse yet, conditions of training that produce rapidly improving performance typically do not produce long-lasting, generalizable learning. As a result, learners and instructors alike can be misled into adopting training or educational experiences that are suboptimal for producing actual learning. Computer-based educational training platforms can counter this unfortunate tendency by providing only productive conditions of instruction—even if they are unintuitive (e.g., spacing instead of massing). The use of such platforms, however, introduces a different liability: being easy to interrupt. An assessment of this possible liability is needed given the enormous disruption to modern education brought about by COVID-19 and the subsequent widespread emergency adoption of computer-based remote instruction. The present study was therefore designed to (a) explore approaches for detecting interruptions that can be reasonably implemented by an instructor, (b) determine the frequency at which students are interrupted during a cognitive-science-based digital learning experience, and (c) establish the extent to which the pandemic and ensuing lockdowns affected students’ metacognitive ability to maintain engagement with their digital learning experiences. Outliers in time data were analyzed with increasing complexity and decreasing subjectivity to identify when learners were interrupted. Results indicated that only between 1.565% and 3.206% of online interactions show evidence of learner interruption. And although classroom learning was inarguably disrupted by the pandemic, learning in the present, evidence-based platform appeared to be immune.

Reducing Central Line-Associated Bloodstream Infection (CLABSI) Rates with Cognitive Science-Based Training

Authors

Jessica Lowery PhD, CIC, FAPIC^a, Matthew Jensen Hays PhD^b, Andrea Burch MS, RN NEA-BC^a, Debra Behr DNP, RN, CCRN-K^a, Steven Brown MD, FACR^a, Elise Kearney RN, BSN, VA-BC^a, Deborah Senseney DNP, RN, RN-BC^a, Sky Arce MSN, RN, PCCN-K^a
aLutheran Medical Center, Wheat Ridge, CO
^bAmplifire, Boulder, CO

Abstract

There have been many tactics throughout the years aimed at reducing central line-associated bloodstream infections (CLABSI) in the healthcare setting. To reduce CLABSI rates at this facility, we employed cognitive science-based online training directed at nursing departments. Following implementation, we found significant reductions in CLABSI rates that were sustained for a minimum of 9 months. These results demonstrate that this learning methodology can be used to help decrease CLABSI and potentially other health care-associated infections.

Training that works, saves lives:

When faced with a rise in deadly bloodstream infections during the height of the COVID-19 pandemic, Ascension Health enacted Amplifire’s eLearning platform to eliminate CLABSI with effective training. Designed to meet learners where they are, Amplifire training has been the difference in saving lives by providing training that lowered CLABSI rates by 79%.

While traditional intervention methods are financially and operationally burdensome, an effective eLearning solution is easy to implement and is respectful of caregivers’ time and knowledge. One-size-fits-all training methods simply cannot keep up with the demands and constraints of modern healthcare. Personalized training, fitted to individuals’ own knowledge gaps, uncertainties, and misinformation is the best way to help employees maximize their potential in their field.

Amplifire uses cognitive and neuroscience principles that are designed to accommodate how people naturally learn, remember, and forget. By tapping into these principles with a virtual, easily implemented, time-and-cost-effective solution, health systems can help their caregivers provide the best possible care and ensure positive outcomes.

Self-Regulated Learning: Beliefs, Techniques, and Illusions

Authors

Robert A. Bjork,¹ John Dunlosky,² and Nate Kornell³

1Department of Psychology, University of California, Los Angeles, California 90095, 2Department of Psychology, Kent State University, Kent, Ohio 44242, 3Department of Psychology, Williams College, Williamstown, Massachusetts 01267

Abstract

Knowing how to manage one’s own learning has become increasingly important in recent years, as both the need and the opportunities for individuals to learn on their own outside of formal classroom settings have grown. During that same period, however, research on learning, memory, and metacognitive processes has provided evidence that people often have a faulty mental model of how they learn and remember, making them prone to both misassessing and mismanaging their own learning. After a discussion of what learners need to understand in order to become effective stewards of their own learning, we first review research on what people believe about how they learn and then review research on how people’s ongoing assessments of their own learning are influenced by current performance and the subjective sense of fluency. We conclude with a discussion of societal assumptions and attitudes that can be counterproductive in terms of individuals becoming maximally effective learners.

The Need for Self-Managed Learning

Our complex and rapidly changing world creates a need for self-initiated and self-managed learning. Knowing how to manage one’s own learning activities has become, in short, an important survival tool. In this review we summarize recent research on what people do and do not understand about the learning activities and processes that promote comprehension, retention, and transfer.

Importantly, recent research has revealed that there is in fact much that we, as learners, do not tend to know about how best to assess and manage our own learning. For reasons that are not entirely clear, our intuitions and introspections appear to be unreliable as a guide to how we should manage our own learning activities. One might expect that our intuitions and practices would be informed by what Bjork (2011) has called the “trials and errors of everyday living and learning,” but that appears not to be the case. Nor do customs and standard practices in training and education seem to be informed, at least reliably, by any such understanding.

Creating Desirable Difficulties to Enhance Learning

Authors

Elizabeth L. Bjork and Robert Bjork
University of California, Los Angeles

Abstract

As teachers—and learners—the two of us have had both a professional and personal interest in identifying the activities that make learning most effective and efficient. What we have discovered, broadly, across our careers in research, is that optimizing learning and instruction
often requires going against one’s intuitions, deviating from standard instructional practices, and managing one’s own learning activities in new ways. Somewhat surprisingly, the trials and errors of everyday living and learning do not seem to result in the development of an accurate mental
model of the self as learner or an appreciation of the activities that do and do not foster learning.

The basic problem learners confront is that we can easily be misled as to whether we are learning effectively and have or have not achieved a level of learning and comprehension that will support our subsequent access to information or skills we are trying to learn. We can be misled by our subjective impressions. Rereading a chapter a second time, for example, can provide a sense of familiarity or perceptual fluency that we interpret as understanding or comprehension, but may actually be a product of low-level perceptual priming. Similarly, information coming readily to mind can be interpreted as evidence of learning, but could instead be a product of cues that are present in the study situation, but that are unlikely to be present at a later time. We can also be misled by our current performance. Conditions of learning that make performance improve rapidly often fail to support long-term retention and transfer, whereas conditions that create challenges and slow the rate of apparent learning often optimize long-term retention and transfer.ˇ

Learning Without Performance and Performance Without Learning

Decades ago, learning theorists were forced to distinguish between learning and performance because experiments revealed that considerable learning could happen across a period when no change was apparent in performance. In latent-learning experiments with animals, for example, periods of free exploration of a maze, during which the animal’s behavior seemed aimless, were shown—once reward was introduced—to have produced considerable learning. Similarly, in research on motor skills, investigators found that learning continued across trials during which the build-up of fatigue suppressed performance.

More recently, a variety of experiments—some of which we summarize below—have demonstrated that the converse is true as well: Namely, substantial improvements in performance across practice or training sessions can occur without significant learning (as revealed after a delay or in another context). To the extent, therefore, that people interpret current performance as a valid measure of learning, they become susceptible to misassessing whether learning has or has not occurred.

Learning Versus Performance: An Integrative Review

Authors

Nicholas C. Soderstrom and Robert A. Bjork
Department of Psychology, University of California, Los Angeles

Abstract

Knowing how to manage one’s own learning has become increasingly important in recent years, as both the need and the opportunities for individuals to learn on The primary goal of instruction should be to facilitate long-term learning—that is, to create relatively permanent changes in comprehension, understanding, and skills of the types that will support long-term retention and transfer. During the instruction or training process, however, what we can observe and measure is performance, which is often an unreliable index of whether the relatively long-term changes that constitute learning have taken place. The time honored distinction between learning and performance dates back decades, spurred by early animal and motor-skills research that revealed that learning can occur even when no discernible changes in performance are observed. More recently, the converse has also been shown—specifically, that improvements in performance can fail to yield significant learning—and, in fact, that certain manipulations can have opposite effects on learning and performance. We review the extant literature in the motor- and verbal-learning domains that necessitates the distinction between learning and performance. In addition, we examine research in metacognition that suggests that people often mistakenly interpret their performance during acquisition as a reliable guide to long-term learning. These and other considerations suggest that the learning–performance distinction is critical and has vast practical and theoretical implications.

The Goal of Instruction

Whether in the classroom or on the field, the major goal of instruction is, or at least should be, to equip learners with knowledge or skills that are both durable and flexible. We want knowledge and skills to be durable in the sense of remaining accessible across periods of disuse and to be flexible in the sense of being accessible in the various contexts in which they are relevant, not simply in contexts that match those experienced during instruction.

In other words, instruction should endeavor to facilitate learning, which refers to the relatively permanent changes in behavior or knowledge that support longterm retention and transfer. Paradoxically, however, such learning needs to be distinguished from performance, which refers to the temporary fluctuations in behavior or knowledge that can be observed and measured during or immediately after the acquisition process.

The distinction between learning and performance is crucial because there now exists overwhelming empirical evidence showing that considerable learning can occur in the absence of any performance gains and, conversely, that substantial changes in performance often fail to translate into corresponding changes in learning.